Sentence examples for multiple expression profiles from inspiring English sources

The MxP shared multiple expression profiles with either the MdP or FNP, and only a few genes showed expression differences specific to this prominence – and most of these were subtle (Figure 18B).

If the mean JSD was greater than 0.25, we combined samples by their sub-facet, producing multiple expression profiles under the names of the sub-facets.

Time-series microarrays capture multiple expression profiles at discrete time points (i.e., minutes, hours, or days) of a continuous cellular process.

Due to capabilities of simultaneous measurement for multiple expression profiles with gradually increasing accuracy and decreasing costs of experiments, those advances in high-throughput microarray and ChIP assays techniques facilitate the corresponding learning and inference of the regulatory maps and even functionality of these genetic networks.

In this method, however, thousands of expression profiles are related with sequence polymorphisms across the genome through their correlated variations, which results in a large number of mappings that make it difficult to consider simultaneously the relationships between multiple genomic regions and multiple expression profiles.

In a seminal study by Lamb et al. [2], a set of genes induced by cyclin D1 in an in vitro model were found to be co-expressed as a group with cyclin D1 mRNA in multiple expression profile datasets of human tumors of various types.

The most crucial aspect of the experimental design is the combination of data from multiple expression profiling methods, genomic sequence and in silico prediction to study miRNA function.

Indeed, searching the Oncomine database (Rhodes et al, 2004) verified that FBXO28 expression was significantly higher in primary breast cancers relative to normal breast tissue in multiple expression profiling studies (Fig 7B and Supporting Information Table S2).

Canonical variates analysis demonstrated that ONFH and non-ONFH bone tissues can be distinguished by the multiple expression profile analysis of numerous genes controlled via canonical TGFB pathway as well as genes coding for extracellular matrix composing collagen type molecules.

Previous studies have yielded less than encouraging false positive and false negative rates resulting from the use of algorithms [ 17, 18] prompting an increasing focus on combining multiple expression profiling datasets with in silico target prediction [ 19].

Another study by Glaysher and colleagues used an ATP-TCA to assess chemosensitivity in 49 surgically-resected NSCLC tumor samples and fit multiple-regression models to explain sensitivity based on multiple gene expression profiles.